Navigating the Hidden Costs and Pitfalls of BigQuery

Google BigQuery is one of the most popular cloud data warehouses. But for certain use cases, BigQuery may not be…well, big enough — or fast enough.

Where BigQuery is optimized only for data warehouse workloads, SingleStoreDB is a great solution when you need to build front-office applications serving analytics on fresh data. It can also handle OLTP workloads.

Navigating the hidden costs and pitfalls of BigQuery

Businesses today face a pressing conundrum: falling into a cost trap with data platforms that promise scalability but fail to deliver on cost predictability. Amongst the sea of data warehouses, Google BigQuery presents a tempting choice with its initial low barrier to entry. But is it the financial iceberg threatening to sink your budget?

The BigQuery paradox: Low entry, high dependency

BigQuery markets itself on accessibility, but this is just the tip of the iceberg. Below the surface lies a complex pricing model that can lead to bill shocks. As businesses scale, they find themselves entangled in a web of compute capacity fees, data processing charges and additional costs for services like the BI Engine and Data Load API. The result? A pricing labyrinth that's as complex as the queries it runs.

A glimpse of the hidden depths

Let’s talk numbers. With BigQuery's on-demand services starting at $5 per TB processed and reserved services at $2,000 per month for 100 slots, it's easy to see why budgeting becomes a guessing game. It’s a challenge to predict the actual cost without empirical data, leading to financial uncertainties that can hamper growth and innovation.

Navigating beyond BigQuery shores

Beyond price, BigQuery may not be big or fast enough for certain use cases. BigQuery is optimized only for data warehouse workloads. With its known limitations in UPDATEs, BigQuery cannot be considered for workflows where the same underlying data is frequently updated or where query latency matters.

Why accept unpredictability when there’s a better way?

SingleStoreDB emerges as the beacon of predictability in the tumultuous seas of data management costs. The question we must ask: Why continue to navigate the murky waters of BigQuery’s pricing when SingleStore offers clarity? SingleStoreDB is a great solution for use cases where you need to run analytics on rapidly moving streaming data, effectively handling both OLAP and OLTP workloads in a single system — without the need for any ETL or data movement.

Top three reasons why customers choose SingleStore over BigQuery

Many organizations initially adopt SingleStoreDB alongside their traditional transactional database or data warehouse. There are three main patterns we see where customers effectively augment — or even replace — BigQuery with SingleStoreDB:

Real-time analytics/ fast dashboards. Ingest data (batch or bulk load) quickly into SingleStoreDB for immediate analysis while continuing to use BigQuery as the primary data warehouse for batch workloads.
End user-facing analytical applications. These applications require very low query latency (sub second) and high concurrency. SingleStoreDB is perfectly suited for this.
Database consolidation. This scenario comprises a mixed set of workloads including transactions, ad-hoc analytics and dashboards. This is where a unified “HTAP” (Hybrid Transactional and Analytical) database can eliminate one or more incumbent databases, while minimizing ETL.

Real customers, real savings

Learn more about ZoomInfo, which turned the tide on operational costs with SingleStoreDB, saving a staggering $1.2 million after moving away from BigQuery.

ZoomInfo Technologies Inc. is a software and data company providing data for companies and business individuals. One of ZoomInfo’s products enables its customers to know what company the users of its customers’ websites work at. This is done by analyzing website user’s IP addresses. Users previously anonymous can now be tagged to a company, transforming this information into leads for marketing and sales teams.

Challenges

ZoomInfo previously leveraged BigQuery for this analysis and the analytics performance was not real time, with slow responses resulting in customer frustration.

ZoomInfo realized that the data platform needed to deliver higher performance at a lower TCO. While evaluating alternative solutions, they found SingleStoreDB perfectly suited their needs with no cloud vendor lock in, high concurrency and easy scale up and scale down. By replacing BigQuery with SingleStoreDB, ZoomInfo realized 24x better performance and 4x lower TCO.

Rising from the depths: SingleStore’s value proposition

SingleStore stands tall as a lighthouse, guiding businesses to safe harbor with its transparent pricing structure and flexibility. The ability to deploy anywhere — be it cloud, on-premises or hybrid environments — translates to freedom from the surprise costs and vendor constraints associated with BigQuery.

In the end, it's about choice. Do you choose to navigate a course fraught with hidden costs and constraints, or do you steer toward a future where cost predictability and operational freedom are not just promised, but delivered?

With SingleStore, the power to make a financially sound and strategically wise data strategy decision is in your hands. Don't let your budget be the next casualty of hidden costs. It's time for a change.

Our technical comparison report “Google BigQuery vs SingleStoreDB” dives deeper into the similarities and key differences between the two platforms.

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